The Fallacy of Fragile State Indices --- Is there a ... · The CIFP fragility index employs a ‘relative structural assessment’ methodology to capture state fragility. It defines

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THE FALLACY OF STATE FRAGILITY INDICES – IS THERE A ‘FRAGILITY

TRAP’?

Mohammad Zahidul Islam Khan, University of Reading

[email protected]

Paper presented at the 66th Annual Political Studies Association Conference,

Brighton, United Kingdom, 21-24 March 2016

Abstract

The concept of state fragility remains elusive despite being in widespread use since early 1990’s and

expressed by a growing trend of indexing sovereign states according to their performances. Different

fragility indices with varied orientations have emerged shaping our perceptions about states

populating the international system. Dominated by domestic drivers of fragility, these indices have

played an important role to universalize the under theorized concept. However, the conceptual

ambiguity and the underlying narrative surrounding these indices demand a critical look at the real

world issue of state fragility and ask : What do these indices actually tell us about the future

trajectories of ‘fragile states’? How long will it take for these states to come out of ‘fragility’ or are

they doomed in a ‘fragility trap’? And if so, is there a more valid analytical framework to investigate

and understand state fragility? Framing the issue in a broader perspective, this paper takes an

‘outside-in’ approach to expose the fallacy of state fragility indices by revealing the ‘fragility trap’

and suggests an alternative framework to investigate and explain the fragile state problematique. It

views the world consisting of Centre and Peripheral sates, where fragility is concentrated mostly in

the later; each nation in turn has its own centre and periphery. The first part of the paper critically

examines four oft-cited state fragility indices (i.e. Bertelsmann Transformation Index, Country

Indicator for Foreign Policy Fragility Index, Fragile State Index, and World Governance Indicator’s

Political Stability and Absence of Violence Index) to identify inadequacies in their conceptualization

and operationalizing of state fragility. Using the fragility scores of different states from the four

indices, the paper estimates the duration the fragile states would take to emerge out of fragility. The

result reveals that, within the conceptual boundaries of these four indices, 23–34% states will require

over 100 years to reach the ‘top’/ ‘sustainable’ status while a staggering 43- 53% states will take

more than 50 years to reach the same threshold and emerge out of fragility if they continue to

maintain their historic trajectories of progress. The findings tend to confirm the existence of ‘fragility

trap’. Introducing the Centre- Periphery model in the second part, the paper contends that,

conceptualizing state only as a functional entity devoid of historicity, power relations, strategic

significance can obscure our understanding on state fragility. The nature of interaction between and

within the Centre and Peripheral state remains the crucial determinant of state fragility. The paper

hypothesizes the propensity of state fragility with four possible variants of interactions within and

between the Centre and Peripheral states. It concludes that a convergence of interest and goals

between the developed Centre and the developing Peripheral states is essential to effectively address

state fragility and ensure a ‘good life’ for the ‘bottom billions’ living in fragile situations. Failing to

do that would make the phenomenon of fragile state a rather inevitable feature of the international

system.

Key Words: Centre-Periphery, Benchmarking states, state fragility, fragility trap, fragile state.


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I. INTRODUCTION

The concept of ''state fragility/weakness1'' remains elusive despite being in widespread use

since early 1990’s and expressed by a growing trend of indexing sovereign states according to

their performance. Different fragility indices with varied orientations have emerged shaping

our thoughts and perceptions about countries that populate the international system. There are

at least 12 such indices developed under the sponsorship of government, business, academia

or non-profit organizations. The major ones include: Fund for Peace’s Fragile (previously

Failed) State Index (FSI), Bertelsmann Transformation Index (BTI), Country Indicator for

Foreign Policy Fragility Index (CIFP), World Bank's Country Policy and Institutional

Assessment (CPIA) rating, World Governance Indicator’s Political Stability and Absence of

Violence (WGI PS&AV) George Mason University's State Fragility Index (SFI), Brookings

Index of State Weakness in Developing World (ISW). These indices have played an

important role in the universal spread of the nascent concept of the fragile state.

While such indices are a welcome addition to the social science literature, the conceptual

ambiguity and the underlying narrative surrounding these indices2 demand a critical look at

the real world issue of state weakness and ask: What do these state fragility indices tell us

about the future trajectories of fragile states? How long will it take for these states to come

out of fragility or are they doomed in a ‘fragility trap’ – defined as state stagnation? And if so,

is there a more valid analytical framework to investigate and understand state fragility?

Considering state formation as a historical process, this paper takes an ‘outside-in’ approach

to investigating and understanding state fragility. The underlying aim of this paper is not to

discredit the narratives espoused by different fragility indices but to frame the issue of state

1 The term ‘state fragility’ and ‘state weakness’ is used interchangeably in this paper as it coexists

with conceptually similar notions like ‘weak state’, ‘failing state’, ‘failed state’ or ‘collapsed state’, all

of which may be defined as different stages along the fragility spectrum. See Endnotes 5, Rice Susan

E. and Patrick Stewart (2008) Index of State Weakness in the Developing World, The Brookings

Institution, MA, Washington, DC and Mata, Javier Fabra and Ziaja, Sebastian (2009:7) in Faust, Jörg

and Nahem, Joachim (eds), ''Users' Guide on Measuring Fragility'', German Development Institute

and the United Nations Development Programme. Available at:

http://www4.carleton.ca/cifp/app/serve.php/1245.pdf/ (accessed on 21 September 2015). 2 See Ziaja, Sebastian (2011), ''What Do Fragility Indices Measure? Assessing Measurement

Procedures and Statistical Proximity'', available at: http://www.die-gdi.de/uploads/media/Ziaja_2012

What_do_fragility_indices_measure_--_manuscript.pdf/ (Accessed on 08 September 2015) and

Sanín, Francisco Gutierrez (2009), ''The Quandaries of Coding and Ranking: Evaluating Poor State

Performance Indexes'', Crisis States Research Centre, Working Paper Number 58.

http://www4.carleton.ca/cifp/app/serve.php/1245.pdf/

http://www.die-gdi.de/uploads/media/Ziaja_2012%20What_do_fragility_indices_measure_--_manuscript.pdf/

http://www.die-gdi.de/uploads/media/Ziaja_2012%20What_do_fragility_indices_measure_--_manuscript.pdf/


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fragility in a broader context. The paper takes a view of the world consisting of ‘Centre’ and

‘Peripheral’ States, where fragility is concentrated mostly in the latter. Each nation in turn has

its own centre and periphery.3 The paper is laid out as follows: firstly it discusses the four

most often cited fragility indices, namely BTI, CIFP, FSI, and WGI and critically examines

how they define and operationalize state fragility to produce the overall composite state

fragility index. Secondly using the fragility scores of different states from the four indices, the

paper estimate the time these fragile states would take to reach the level of a strong/stable

state to emerge out of fragility. The result reveals that, within the conceptual boundaries of

these four indices, it will take hundreds of years for many states to come out of fragility –

essentially proving the existence of a ‘fragility trap’. Finally the paper suggests an alternative

analytical framework to investigate and understand state fragility based on the Centre-

Periphery model. The paper concludes that the current quantitative measures used for

assessing state fragility need to sufficiently include the external drivers of fragility; a

convergence of ‘interest and goals’ between the developed ‘Centre’ and the ‘Peripheral’

fragile states is essential to decrease the ‘gap’ and effectively address the problem of state

fragility. Failing to do that would make the phenomenon of ‘fragile states’ a rather inevitable

feature of the international system.

II. STATE FRAGILITY INDICES

The rapid transnational diffusion of the concept of ‘fragile state’ was largely made possible

by different oft quoted fragility indices. Such indices came handy particularly for the policy

makers, commentators and analysts as it provided quantified scores and rankings to each state

based on their (perceived) overall fragility. The stated aim of these indices is to capture

government responsibilities commonly considered as ‘core functions’ of statehood. States are

assessed against a set of criteria that represents such core functions. The ranking and scores of

the indices reveal which state is doing better compared to the others. A brief discussion on

four fragility indices analysed in this paper is given below.

3 See for details, Gordon Marshall (1988). "Centre-Periphery Model" A Dictionary of Sociology.

Available at <http://www.encyclopedia.com> (accessed on 10 October 2015)

http://www.encyclopedia.com/


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Bertelsmann Transformation Index (BTI)4

The BTI relies on qualitative expert survey by country experts on a scale of 1(worst) to 10

(best) to index 129 developing and ‘transitional states’5 about how they are steering social

change toward democracy and market economy. Successful ‘transformation’ is defined as a

‘politically driven change’ towards having a ‘functioning administration structures’, ‘securing

monopoly on the use of force’, ‘resource efficiency’, ‘building consensus’ to materialize

transformation goal and working reliably with external supporters an neighbours by the state

(BTI 2014b:123).The final BTI ranking is the aggregate of ‘Status Index’ and ‘Management

Index’. Status Index focuses on a state’s political and economic transformation while the

Management Index reportedly assess the acumen with which decision-makers steer political

processes towards democracy and market economy. Score for political transformation in

Status Index is derived from the scores assigned by the country experts in response to 18

questions grouped under five criteria. For example, to measure a state’s monopoly on the use

of force, the question posed is: ‘To what extent does the state’s monopoly on the use of force

cover the entire territory of the country?’ Country experts assign a score (between 1-10)

based on the degree and geographical extent to which the state is able to exercise the

monopoly on the use of force. Similarly, the assessment of economic transformation is

derived from 14 indicators based on seven criteria related to the level of socioeconomic

development, market, currency and price stability, property rights, welfare regime, economic

performance and sustainability. The ‘Management Index’ focuses on five criteria: structural

difficulties, steering capability, resource efficiency, ability to build consensus and

international cooperation. These are derived through a total of 20 indicators out of which 3

are quantitative (i.e. GNI per capita in PPP terms, UN Education Index and average of BTI

score on Stateness and Rule of Law criteria). In total there are 52 indicators grouped under 17

criteria against which scores are assigned for each state to produce the overall ranking.

Emphasizing the importance of core governmental functions, a state is classified as ‘failed’

when the arithmetic mean of the scores given for monopoly on the use of force and basic

4

See BTI (2014a) Codebook for Country Assessments and BTI(2014b) Methodology available at

http://www.bti-project.org/bti-home/ (Accessed on 15 September 2015) 5Number of ‘developing’ and ‘transitional’ countries surveyed has increased from 116 in 2003 to 129

in 2014 as it includes countries with population over two million; additionally seven states are

included as particularly interesting cases (BTI 2014a: 4; 2014b: 125). BTI excludes all Organisation

for Economic Cooperation and Development (OECD) countries ‘assuming’ that ‘reforms needed in

these OECD countries towards democracy and market economy would differ’ compared to those that

are yet to achieve a fully consolidated democracy and market economy.


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administration (under ‘stateness’ criteria of Status Index) is less than three. Only two

countries (Central African Republic and Somalia) appear as ‘failed’ in BTI 2014.

Country Indicator Foreign Policy (CIFP) Fragility Index6

The CIFP fragility index employs a ‘relative structural assessment’ methodology to capture

state fragility. It defines state fragility as ‘‘the extent to which the actual institutions,

functions and processes of a state fail to accord with the strong image of a sovereign state, the

one ratified in both state theory and international law (Carment et. al 2010:84).’’ According

to CIFP, fragile states lack the functional authority to provide basic security within their

borders, the institutional capacity to provide basic social needs for their populations, and/or

the political legitimacy to effectively represent their citizens at home and abroad. Failed states

are characterized by conflict, humanitarian crises, and economic collapse. Government

authority, legitimacy, and capacity no longer extend throughout the state, but instead are

limited either to specific regions or groups.

CIFP fragility index uses 84 indicators grouped into six clusters: Governance, Economics,

Security and Crime, Human Development, Demography, and Environment. The data is then

reprocessed through the ALC (Authority, Legitimacy, and Capacity) framework, where any

weaknesses in one or more of the ALC dimensions are considered to have an impact on the

overall fragility of the state. For global ranking the best performing state receives a score of

one, the worst a score of nine, and the rest are continuously distributed between worst and

best values based on their relative performance. To account for the abrupt variations in data

due economic shocks, natural disasters and other externalities, a five year average is taken for

global ranking score. Once all indicators have been indexed using this method, the results for

a given country are then averaged in each subject cluster to produce the final scores for the

country. According to CIFP, a score of 6.5 or higher reflects that a country is ‘performing

poorly’ relative to other states. Such a score may be indicative of an arbitrary and autocratic

government, a history of non-transparent government, the presence of significant barriers to

political participation, the absence of a consistently enforced legal framework, or a poor

human rights record. Conversely, a score between 1- 3.5 indicates that a state is ‘performing

well’ relative to others. Scores in the moderate 3.5 to 6.5 range indicate state’s performance

6 See Carment, David, Stewart Prest and Samy Yiagadeesen (2010), Security Development and the

Fragile State: Bridging the gap between theory and policy, Routledge, London. p.84-112 and the

‘Failed and Fragile States’ section of the CIFP website http://www4.carleton.ca/cifp/ffs.htm/

(accessed on 19 September 2015)

http://www4.carleton.ca/cifp/ffs.htm/


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approaching the ‘global mean’. According to CIFP 2012 index, 14 countries are ‘performing

well’, 40 are ‘performing poorly’ and the remaining 144 are within the ‘global average’.

Fragile State Index (FSI)7

The widely cited fund for peace FSI defines ‘fragile states’ in terms of negative attributes

such as: loss of physical control of its territory or a monopoly on the legitimate use of force,

erosion of legitimate authority to make collective decisions, an inability to provide reasonable

public services, and the inability to interact with other states as a full member of the

international community. The Index is based on content analysis using its proprietary Conflict

Assessment System Tools (CAST) software which reportedly distils millions of pieces of

relevant information into an ‘easily digestible and informative format’ for 178 countries. To

operationalize the concept, each state is apportioned a score on twelve key political, social

and economic indicators based on the scale of 0 (best) - 10 (worst). Thus a country’s total

score is out of 120 where a higher score indicates greater fragility. Out of twelve indicators,

four (demographic pressure, refugees and internally displace people, group grievance and

human flight and brain drain) appears under social dimension, two (uneven economic

development and poverty and economic decline) under economic and six (state legitimacy,

public service, human rights and rule of lw, security apparatus, factionalized elites and

external intervention) is placed under political and military dimension. All indicators are

given equal weight. The final fragility score is calculated by adding the scores. FSI also

categorizes countries into groups like ‘alert’ (score 100.1-120), ‘warning’ (score 60.1 -100),

‘moderate/stable’ (score 30.1- 60) and ‘sustainable’ (0-30). In 2015 FSI, 16 countries were

categorized in alert state, 109 in warning, 38 in stable and 15 in sustainable category.

World Governance Indicators - Political Stability & Absence of Violence (WGI - PS &

AV)8

The WGI is the largest geographical and temporal coverage of all fragility indices yet.9 It

defines governance as “the traditions and institutions by which authority in a country is

exercised. This includes (a) the process by which governments are selected, monitored and

7 See Methodology available at: http://fsi.fundforpeace.org/methodology/ and Fragile State Index

2015, available at: http://library.fundforpeace.org/fsi15-report/ (accessed 22 September 2015). 8 Kaufmann, Daniel., Kraay, Aart., and Mastruzzi, Massimo., (2010)., The Worldwide Governance

Indicators, Methodology and Analytical Issues., Policy Research Working Paper 5430, The World

Bank, Development Research Group, Macroeconomics and Growth Team, September 2010. 9 Coverage increased from the initial 180 in 1996 to 215 countries and territories in 2013 index.

However, in this paper data of 198 countries have been used to facilitate cross index comparison.


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replaced; (b) the capacity of the government to effectively formulate and implement sound

policies; and (c) the respect of citizens and the state for the institutions that govern economic

and social interactions among them.’’ Kaufmann, Kraay, and Mastruzzi (2010: 4). There are

two measures of governance corresponding to each of these three areas resulting in a total of

six dimensions of governance indices. Out of these six, the index on Political Stability and

Absence of Violence closely proxies the state fragility10

as it aims to capture the perceptions

of the likelihood that the government will be destabilized or overthrown by unconstitutional

or violent means, including domestic violence and terrorist acts. The expert data / opinion

polls are assimilated in 6 indicators from 31 sources which include survey institutes, think

tanks, non-governmental organizations, international organizations, and private sector firms.11

The index scale is about -2.5(worst) – 2.5(best) expressed with associated standard error for

each country. It also reports the overall position of a country in terms of ‘percentile rank’

where 0 is the lowest and to 100 is the highest rank and reports the lower and upper bounds of

90% confidence interval for governance. Thus, Bangladesh with an estimated score of -1.61

in the Political Stability and Absence of Violence 2013 index has a percentile ranking of 7.58

amongst the 215 states/entities.12

The wide coverage of the index has made it a very

frequently used measure in statistical analysis. However, the ‘state centrism’, along with the

possibility of bias generated through the expert opinion remains its main weaknesses.

What Do the Fragility Indices Really Measure?

Table 2.1 lists the periodicity, broad orientation, weighting of each indicator and the extent of

externalities captured in these four indices. Several trends emerge from this simple tabulation:

First, the coverage of some indices is selective as BTI exclude the OECD countries. Such

exclusions, valid or not, recognize the case/class specificity to measure state fragility. Second,

the varied periodicity raises the question of specifying the time interval in which fragility

should and can be measured. Third, BTI and CIFP tend to emphasize the developmental

aspects while FSI and WGI are stability and security orientated. However, all four indices

10

See Mata and Ziaja (2009: 76). 11

Number of data sources consulted varies from 1 to 9. Data sources includes : African Economic

Outlook, Business Environment Risk Intelligence, CIRI Human Rights Data Project, Economist

Intelligence Unit, Global Insight Global Risk Service, iJET, Institute for Management Development,

Institutional Profiles Database, Merchant International Group, Political Risk Services, Political Terror

Scale, World Economic Forum. 12

The upper and lower limit of the ‘percentile rank’ for Bangladesh is 11.32 and 4.72 respectively

while the standard error of the ‘estimated score’ is .23.


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take a 'maximalist' approach by including a wide number of domestically orientated state

centric attributes. But how much do these indices really tell us about state fragility?

Table 2.1: Selected features of four fragility indices

Index Periodicity

(Published)

Orientation and approach

of the Index

Indicators

Weighting

External Dimensions

BTI Every 2 yr

(2003 and

since 2006)

State Centric, largely

domestic factors driven.

Focus on democracy and

market economy; Expert

opinion based; ‘Maximalist’

Equal

weight

‘International Cooperation’-

one of the 17 criteria. Focus on

political actor’s ‘‘willingness to

cooperate with outside

supporters and organizations.’’

CIFP Unknown

(2008,2010,

2011,2012)

State Centric, domestic

factors driven. Focus on

developmental aspects.

‘Maximalist’

Equal

weight

No explicit mention of

measures/ indicators

FSI Yearly

(Since

2005)

Largely domestic factors

driven. Focus on stability

aspect; ‘Maximalist’

Equal

Weight

‘External Intervention’ as one

of the 12 dimensions. Includes

pressures and measures related

to: Foreign Assistance,

Presence of Peacekeepers,

Presence of UN Missions,

Foreign Military Intervention,

Sanctions and Credit Rating.

WGI Yearly

(Since

1996)

Entirely domestic factors

driven. Focus on Security,

Expert opinion and survey

based; ‘Maximalist’

between

0.010 and

0.094

No explicit mention of

measures / indicators.

Source: Author’s compilation.

Firstly, the tendency of the state fragility indices to discount the external origins of fragility is

indeed confounding. 13

Whatever limited externalities captured in these indices bears a very

little cumulative impact on the overall score and often reflect an assumption that external

factors are always positive. Indeed the fact that many global factors may have pernicious

impacts contributing towards fragility is not sufficiently recognized in these models. States in

an international system belong to the international society which can bring both progressive

and regressive impact affecting its performance. The proximity or geopolitical significance of

a resource rich peripheral state/region may draw more attention of the major powers;

similarly a peripheral state that has prematurely liberalized its economy under the

prescriptions of World Bank/IMF or adopted a floating foreign currency exchange rate may

be more affected by the exogenous shocks. Relegating fragile states’ susceptibility to external

factors as a ‘potential reflection of state weaknesses’ is simply not the answer in a world

13

As Gros (2011:549) argued ‘‘Why contemporary literature on failed state has tended to discount the

external origins of state failure is baffling.’’ Also see OECD (2012) Think global, act global:

Confronting global factors that influence conflict and fragility.


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structured in a Centre-Periphery model. In a globalized world, there are major economic,

security and environmental issues that cannot be dealt independently by individual or a group

of states. The capacity of the international system is equally important. For example the

methodology used by Department of Economic and Social Affairs of the UN Secretariat for

Least Developed Country (LDC) includes ‘remoteness’ criteria under the Economic

Vulnerability Index that recognizes the need to focus on those sources of vulnerability that

‘‘(a) accentuate or perpetuate underdevelopment, (b) not the result of misguided policies but,

instead, are such that they limit policymakers’ capacity to respond to shocks, and (c) are

beyond a country’s control.’’14

Remoteness is a structural obstacle to trade and growth and a

possible source of vulnerability. Countries situated far from major world markets face a series

of structural handicaps that may render them less able to respond to shocks in an effective

way or to diversify their economies. Again, between 2003 - 2012 the emerging economies

lost USD 6.6 trillion in illicit financial flows to the developed world which was more than the

official development assistance (ODA) and the Foreign Direct Investment (FDI) combined.15

Thanks to the globalization, the trend of illicit outflows is increasing at a staggering average

rate of 9.4 percent per year. The current fragility indices do not take into account such factors

that are often beyond a country’s control. Similarly, the indices take into account the

‘presence of UN troops’ as a potential reflection of fragility but does not credit the states

contributing large number of troops in UN missions in their assessment of fragility.

Secondly, the absence of a consensus on what constitutes a ‘strong state’ contributes to the

conceptual vacuum of operationalizing state fragility. Indeed the term ‘fragile states’

inherently implies a hierarchy -- an expression of power, that some states are more capable

then the others in fulfilling the ‘idealized’ functions of a state. Implicit in this idealized image

of state lies the Western model -- a fixed prescriptive that informs most development and aid

activities in fragile states. Such definitional inadequacy amount to 'prototyping' and rating the

'others' and restricts the use of such indices for macro-quantitative research.16

14

See CDP and UN DESA (2015:53-58) Handbook on the Least Developed Country Category:

Inclusion, Graduation and Special Support Measures Second Edition., Available at:

http://www.un.org/en/development/desa/policy/cdp/cdp_ldcs_handbook.shtml/ (Accessed on 27

October 2015) 15

The ODA to the developing countries from 2003 to 2012 was just US$ 809 billion and the FDI was

US$ 5.7 trillion over the same 10-year period. See Dev Kar and Joseph Spanjers (2014: vii) Illicit

Financial Flows from Developing Countries: 2003-2012, Global Financial Integrity. 16

See Pureza, Jose Manuel., Duffield, Mark., Mathews Roobert., Woodward, Susan and Sogge,

David., (2006) Peace Building and Failed States: Some Theoratical Notes, Expert Meeting paper on

http://www.un.org/en/development/desa/policy/cdp/cdp_ldcs_handbook.shtml/


10

Thirdly, the indicators often include both (assumed) causes and consequences of fragility (Di

John, 2008, Pureza et al, 2006). For example, a high score in the explanatory variables like

the child mortality, voice and accountability etc. used in most indices are indirect indicators

that a state may be weak while their heterogeneous dependent variables like incidence of

coup, conflict intensity etc. reflects the disastrous consequence of state weakness (King and

Zeng 2000, Sanin, 2009); lumping these as indicators stand as ‘‘an elaborate and unsupported

hypothesis’’ questioning the construct validity of the indices.

Fourthly, it is often unclear whether the fragility captured in these indices is attributed to the

society as a whole or only to the state and its institutions. While the sate-society bond is a

vital 'relational' attribute, putting them under a homogeneous scale of measurement could be

misleading. In the context of state, fragility tends to reflect the property of a political system;

but, when fragility refers to society as a whole, it becomes a property of society and thus,

being defined much more broadly including any kind of political, social or economic

instability (Mata and Ziaja, 2009:6). What matters in one society may not have similar

significance in another. For example in the domestic context, a religion related social

indicator like ‘clerical approval’ in Iraq or Syria would not mean the same in Japan or USA.

Fifthly, the disaggregation of the concept into 'measurable' attributes is also fraught with high

level of abstraction. The ALC framework introduced in the CIFP is a welcome addition; other

indices also include these functions but they subsume them under different dimensions.

However, measuring a latent concept like legitimacy is much more difficult than measuring

service provision; as a result, the CIFP has to revert to traditionally available indicators like

the quality of democracy as measured by the Polity Index – and these indicators can often be

culturally biased. Except for the function like 'monopoly on the use of force', perception and

standard about other state's functions and public services varies widely. Inclusion of

benchmarks that go beyond the core issues, like ‘economic policy’, ‘ease of doing businesses’

further diverge the opinion reducing these indices to an opaque summary measurement. Table

2.2 below summarizes the limitations of the four fragility indices.

''Peacebuilding Process and State Failure Startegies'' organized by Peace Studies Gorup and Ford

Foundation, 31 March- 01 April 2006 and Di John, Jonathan (2008), ''Conceptualising the Causes and

Consequences of Failed States: A Critical Review of the Literature'', Crisis States Research Centre,

School of Oriental and African Studies. Available at: http://www.isn.ethz.ch/Digital-

Library/Publications/Detail/?&lng=en&id=57427/ (Accessed on 27 October 2015)


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Table 2.2: Brief Summary of Limitations of State Fragility Indices

Areas Limitations

Conceptual The idealized image of state mirrors a Weberian model as such the classification

(often) viewed as an ‘expression of power’.

‘Thin’ conceptualization emphasizing state’s functionality/performance over

historicity and the deep (external) structures in which state is embedded.

Both state and society placed under a homogeneous scale of measurement which

could be misleading.

Ignore the reality and explanatory importance of irreducible and potentially

unobservable international structures that can generate fragility.

Reflects ‘methodological individualism’ with state in the centre and action of

human agency underpinning fragility as if states are ‘actors without systems’.

Operationalizing Fragility is reduced to state’s function/ performance on security, economic,

political, social and environmental dimensions.

Little or no regards to the effects of international structures, externalities, strategic

environment within which a state operate.

Ignores possibilities of reverse causation, i.e. possibility of (international) structures

that are beyond states’ control accentuating fragility.

Indicators

selection

Numerous domestically focused indicators as proxy.

Include both (assumed) causes and consequences of fragility.

‘One size fits all’ approach.

Data

Aggregation

Fraught with high level of abstraction.

Equally weighted indicators and aggregation methods tend to blur the distinctions

between ‘necessary’ and ‘sufficient’ conditions.

Latent concepts (i.e. legitimacy) could be culturally biased.

Data Sources Use of similar data sources poses a danger of conflation and of redundancy.

Survey based index (BTI) are subjective to the interpretation of the ‘experts’.

A nuanced understanding of state fragility arguably requires historicising and contextualizing

the fragile state problematique taking into account the dynamics of external and internal

dimensions. State making is a historical process and the strategic environment in which this

process takes place has a profound impact on a state’s future trajectory. To illustrate using a

simple example from the microeconomic theory: we know that the price is higher and the

output is lower in a monopolized market than in a competitive one. In both markets, the

attributes of the actors (i.e. the firms in this case), are identical: every firm tries to maximize

its profits and consequently produces the level of output at which marginal cost equals

marginal revenue. However, what accounts for the variation in price and output between these

markets is not variation in the attributes of the units (i.e. firms) but variation in the

environments or market structures (i.e. monopoly vs competitive) in which they act.

Similarly, in the ‘world market of states’ the ‘strategic environment’ in which a state operates

can have a greater impact on state’s performance and future trajectory.

Notwithstanding the imprecise combination of variables and the danger of conflation and of

redundancy due to a higher dependency on the expert survey data, these four indices do

capture some features of state fragility. The high correlation amongst these four indices (bi-


12

variate correlation coefficient ranging between 0.8 - 0.9)17

reflects that, within their

conceptual boundaries, they do measure some aspects of ‘state fragility’. However, this does

not mean causation and could also be due to the fact that they use highly similar data sources.

Such ambiguities aside, the central question is perhaps to investigate the future trajectories of

these states categorized as ‘fragile’ in these four indices. In other words, is there a hope for

these countries to come out of fragility in near future or are they doomed in a fragility trap?

III. IS THERE A ‘FRAGILITY TRAP’?

‘Fragility trap’ implies a condition of state stagnation -- that the state that has been

categorized as ‘fragile’ will remain stuck in that condition for considerable period of time

and their prospect of coming out of fragility, if at all, is severely limited. Within the

conceptual boundaries of the fragility indices, each state is assigned with a score that reflects

its current status attained over a period of time since its independence. To determine whether

a ‘fragility trap’ exists or not, we need to find out whether the countries that are categorized

as ‘fragile’ will ever be able to attain a pace of improvement that would place them alongside

the top ranking ‘stable and strong’ states and if so in how many years. If the results show that

it would take an exponentially high duration for the ‘fragile states’ to reach that threshold,

then we could conclude that the current narrative of the state fragility indices supports the

existence of ‘fragility trap’. Pritchett et. al. (2010) take a similar approach to confirm

‘capability trap’. Using a variety of empirical indicators of states’ administrative capability,

they demonstrate that many states are stuck in ‘capability traps’ as their implementation

capability is both severely limited and improving (if at all) in a snail pace.18

According to

Pritchett et. al. (2010) states like Haiti or Afghanistan would take hundreds (if not thousands)

of years to reach the capability of Singapore and decades to reach even a moderate capability

country like India. However, their focus is on the administrative capability of the states as

such they use data that reflects countries administrative capability namely ‘Quality of

Government’ score from the International Country Risk Guide, ‘Government Effectiveness’

score from Kaufmann, Kraay and Mastruzzi (2009), ‘Progressive Deterioration of Public

Services’ from FSI and scores on ‘Resource Efficiency’ from the BTI. Our focus is on

‘fragility’ which encompasses, among others, the capability dimensions as captured in the

data of different fragility indices.

17

See Mata and Ziaja (2008:29). 18

See Lant Pritchett, Michael Woolcock, and Matt Andrews (2010:13-18) Capability Traps? The

Mechanisms of Persistent Implementation Failure, Working Paper, Centre for Global Development.


13

Data and Methods

Considering state consolidation as a historical process, this paper investigates the rate of

progress of these states since independence and attempts to predict the length of time in years

which would be require for states to emerge from their fragile status. The calculation is

performed in 2 stages:

a. The first stage is to create a comparable scale for all four indices to simplify

comparison. Thus all index scores are converted to an ascending scale of 0 – 10 expressed

to 3 decimal places. This is achieved in two steps: first converting the fragility score in

CIFP and FSI in ascending scale as they are rated on a descending scale with the worst

performing countries being assigned the highest scores. Thus, Somalia’s (the worst

performer) score of 114.0 out of 120 in FSI 2014 becomes (120.000 -114.000) = 6.000 and

the same in CIFP 2012 index for Somalia is (9.000 – 7.810) = 1.190.

Second, rebasing these country scores in a comparable scale of 0 – 10 is achieved by

using the formula: {(New Maximum - New Minimum) ÷ (Old Maximum - Old

Minimum)} x (Country Score – Old Minimum) + New Minimum. Since the new scale is

0 -10, the new minimum is always 0 and the new maximum is always 10. The Old

maximum and minimum refers to 120 and 0 in FSI, 1 and 9 in CIFP, 20 and 1 in BTI (as

the aggregate value of Status and Management index is taken) and -3 and +3 in WGI

(inclusive of standard error). Thus, Somalia’s fragility score of 6.000 in FSI 2014

becomes [{(10-0) ÷ (120-0)} x (6-0) +0] = .5 and the score of 1.190 for Somalia in CIFP

2012 index becomes 1.488 in the new comparable scale of 0-10.

b. The second stage of the calculation involves deriving the number of years for each

country to emerge from fragility. It also requires multiple steps and assumptions. First is

to establish a threshold score that a country needs to attain in future which is indicative

that it has emerged from fragility. One clear threshold score will be to the ‘top’ ranking

country of that particular index. A second and more moderate threshold will be to take

the global average fragility score of the index and estimate the years required to reach

that status. However, for FSI, the lowest threshold of ‘stable’ and ‘sustainable’ status – as

defined in that index would be a more appropriate and conservative threshold to consider.

Thus for each index, we define two thresholds as follows:

BTI: Rescaled score of the ‘top’ scoring country, Taiwan (8.63) and the

global average (5.302).


14

CIFP: Rescaled score of the ‘top’ scoring country, Switzerland (8.463) and

the global average 5.264.

FSI: lowest threshold of ‘stable’ states which corresponds to a score of 30,

rescaled to 5, and the lowest threshold of ‘sustainable’ states which

corresponds to a score of 60, rescaled to 7.5.

WGI: Rescaled score of the ‘top’ scoring country, Greenland (8.19) and the

global average (4.93).

Second step is to establish the number of years between the year of independence of each

country and the year of the relevant index. Using the date for each country from the

COW v.2011 datasets the number of years which elapsed between independence and the

year of the index is calculated by subtracting the former from the latter.

Third step is to establish the annual rate of progress for each country within each index.

Here we are confronted with two problems. First is to guess what could have been the

score for a country at its independence? Indeed, some states could have had a better start

while others might have had started from zero. However, this paper makes an optimistic

assumption that the lowest score of a country at independence could have been the same

as the ‘worst performer’ in that index. If a state’s score was higher at the time of

independence, this would overstate the duration at which that country could came out of

fragility. Conversely, an understatement is possible if the country had a substantially low

starting point – which, given the score of the ‘worst performers’ in all four indices is

highly unlikely. Thus, it is an optimistic assumption.19

The second problem is to decide what measures to apply – i.e. simple average or

compound average rate, for calculating the annual rate of progress. To derive a simple

average annual rate of progress for each country in an index, the score of the ‘worst

19

To illustrate with an example, let us consider the case of Pakistan, independent state since 1947,

having a rescaled score (in 0-10 scale) of 1.425 in the FSI 2015 index. The rescaled score of the worst

performer in FSI 2015 (i.e. South Sudan) is 0.458. Thus Pakistan’s historic rate of progress out of

fragility is (1.425 -0.458)/67 = 0.014. At this rate Pakistan would take 248 yrs to become stable and

421 years to reach sustainable status. However, if we consider that Pakistan had a better start in 1947

compared to South Sudan and had a better fragility score, say 1 instead of 0.458, then its historic rate

of progress after 67 years would be (1.425 – 1)/67 = .0063. At this rate Pakistan would take 563 years

to become stable and 878 years to reach sustainable status – both of which are higher compared to the

previous estimate. Thus taking the score of the respective worst performers in each index as the score

at independence for all countries is an optimistic assumption.


15

performer’ in that index is subtracted from the country’s present score and the result is

divided by the ‘years since independence’. Again, a compound annual growth rate

(CAGR) could be derived by using the formula: {(Ending Year Value/ Beginning Year

Value) 1/Years since Independence

- 1} where the beginning year value for a country is substituted

by the score of the ‘worst performer’ in that index. However, forward projection for

countries using the CAGR formula depicts more number of courtiers requiring greater

number of years to come out of fragility in each index.20

Thus we consider the simple

average provides the most optimistic estimate of a country’s annual pace of progress and

calculate it using the following formula:

1. Optimistic Annual Rate of Progress = ( Current Fragility Score - Score of the ‘worst

performer’ in that index ) / Year Since Independence

Finally, having established an optimistic annual rate of progress, we can now make a

forward projection for each country. The result gives us the number of years required to

reach the desired threshold based on the country’s historic trajectory. This is achieved by

dividing the difference between the desired threshold score (as defined above) and

county’s current fragility score with the ‘optimistic annual rate of progress’ using the

following formulas:

2. Years to reach ‘Top’ = ( Fragility Score of the ‘Top’ Country – Country’s Current

Fragility Score) ÷ Annual Rate of Progress ......................................(for CIFP, BTI and WGI )

3. Years to reach the lowest threshold of ‘Stable’ state = (5 - Country’s Current Fragility

Score) ÷ Annual Pace of Progress. ....................................... ......(For FSI 2015 index)

4. Years to reach the lowest threshold of ‘Sustainable’ state = (7.5 - Country’s Current

Fragility Score) ÷ Annual Pace of Progress. ................................(For FSI 2015 Index)

5. Years to reach Global Average = (Global Average Fragility Score - Country’s Current

Fragility Score) ÷ Annual Pace of Progress. ......................(For CIFP, BTI and WGI)

20

CAGR reflects a ‘smoothed’ annual progress as it does not capture ‘volatility’. However, compared to the

simple annual average, CAGR predicts a more daunting picture for countries to emerge from fragility. For

example, in BTI 2014, a simple average estimate predicts only 36 countries requiring more than 100 years to

reach the ‘top ranking country’ while the number of countries increases to 88 if we use the CAGR formula. In

case of FSI, the use of CAGR estimates 45 countries requiring more than 100 years to become ‘stable’ compared

to a prediction of 31 countries using the simple average estimate.


16

Validity and Reliability of the Calculation Method

At this point, we check the validity of our method of calculation. First, we check the

correlations amongst the four indices. It is revealed (see table 3.1) that all four indices retain

strong positive correlations after rescaling (correlation coefficient ranges from .663 to .955).

We also find strong correlations in ‘optimistic annual rate of progress’ amongst the four

indices (see table 3.2). The correlation coefficient of the Optimistic Annual Pace of Progress

ranges from .695 (between WGI and FSI ) to 0.98 (between FSI and CIFP).

Table 3.1: Correlation of the rescaled fragility scores of four indices

Table 3.2: Correlation of the optimistic annual rate of progress of four indices

WGI (2013)

Optimistic

Annual Pace of

Progress

CIFP (2012)

Optimistic

Annual Pace of

Progress

BTI (2014)

Optimistic

Annual Pace

of Progress

FSI (2015)

Optimistic

Annual Pace of

Progress

WGI (2013) Optimistic

Annual Pace of Progress

Pearson

Correlation 1 .734

** .877

** .695

**

Sig. (2-tailed) .000 .000 .000

N 181 180 129 178

CIFP (2012) Optimistic


Pearson

Correlation .734

** 1 .855

** .980

**

Sig. (2-tailed) .000 .000 .000

N 180 180 129 178

BTI (2014) Optimistic


Pearson

Correlation .877

** .855

** 1 .804

**

Sig. (2-tailed) .000 .000 .000

N 129 129 129 127

FSI (2015) Optimistic


Pearson

Correlation .695

** .980

** .804

** 1

Sig. (2-tailed) .000 .000 .000

N 178 178 127 178

**. Correlation is significant at the 0.01 level (2-tailed).

WGI 2013

Rescaled

Fragility Score

on 0-10 Scale

CIFP 2012

Rescaled

Fragility Score

on 0-10 Scale

BTI 2014

Rescaled

Fragility Score

on 0-10 Scale

FSI 2015

Rescaled

Fragility Score

on 0-10 Scale

WGI 2013

Rescaled

Fragility Score

on 0-10 Scale

Pearson Correlation 1 .791** .663** .830**

Sig. (2-tailed) .000 .000 .000

N 181 180 129 178

CIFP 2012

Rescaled

Fragility Score

on 0-10 Scale

Pearson Correlation .791** 1 .777** .955**

Sig. (2-tailed) .000 .000 .000

N 180 180 129 178

BTI 2014

Rescaled

Fragility Score

on 0-10 Scale

Pearson Correlation .663** .777** 1 .762**

Sig. (2-tailed) .000 .000 .000

N 129 129 129 127

FSI 2015

Rescaled

Fragility Score

on 0-10 Scale

Pearson Correlation .830** .955** .762** 1

Sig. (2-tailed) .000 .000 .000 N

178 178 127 178

**. Correlation is significant at the 0.01 level (2-tailed).


17

Second, to check the internal validity of our method of calculation, we compare the ‘actual

fragility scores’ of a particular year in the past with the ‘predicted fragility score’ of the same

year derived by using our method. A strong positive correlation between the two scores

would imply that our predicted fragility score is not derived ‘by chance’ and validate our

method. Accordingly we select the oldest year (i.e. 2003 for BTI, 2010 for CIFP, 2006 for

FSI and 1996 for WGI) of which data is available for comparison in each index for the bi-

variate correlation. The results are listed in table 3.3. Indeed, (see table 3.2 below) we find

that the predicted score obtained by the method used in this paper is strongly correlated with

the actual score. In case of BTI 2003 the correlation coefficient (r) is .716 (N= 116, p < .01),

for CIFP 2010, r =.958 (N=190, p < .01), for FSI 2006, r=.944 (N=190, p < .01) and for WGI

(PS&AV) 1996, r=.531 (N=185, p < .01). In case of WGI (PS&AV), correlation coefficient

increases to .67 when comparing with the data of the year 2000. This tends to confirm that the

fragility scores for each country calculated by using our method are fairly accurate and does

not happen by chance. In other words, if the predicted fragility score derived for a past year is

strongly associated with the actual score, it is likely that the predicted fragility score for the

future years will also be similar.

Table 3.3: Bi-variate correlation between the ‘actual’ and ‘predicted’ fragility scores of four indices21

Predicted Fragility Scores of

Actual Fragility Score of BTI -2003 CIFP 2010 FSI 2006 WGI 1996

BTI -2003 .716***

CIFP 2010 .958***

FSI - 2006 .944***

WGI 1996 .531*** *** Correlation is significant at 0.01 level (2 tailed)

Results and Analysis

The results involving all 197 states in four indices revealing how many years they will take to

reach the ‘sustainable/top’ and ‘stable/global average’ threshold is placed at annex A. It is

evident that a great majority of these states are stuck in a fragility trap. Table 3.2 below is a

snapshot of annex A involving 15 most fragile states that appear in all four indices. It shows

that, given their current pace of emerging out of fragility, all 15 states will require over

hundred years to reach the ‘top’ ranking country or stable/sustainable status. For example,

Syria would require 625 years to become ‘sustainable’ (according to FSI), 1398 years to reach

21

To calculate ‘predicted’ score, the lowest score of the respective index is taken as the score at independence

and the remaining year’s score are calculated by multiplying it with the respective ‘optimistic pace of

progresses’ as per the calculation methods used in this paper.


18

at par with Taiwan (according to BTI), 168 years to reach Switzerland (according to CIFP)

and 3825 years to reach Greenland (according to WGI). Again, according to the FSI Pakistan

would require 248 years to become ‘stable’. According to the BTI it would take 185 years for

Pakistan to reach the status of Taiwan while a forward projection of CIFP ratings predicts 198

years to reach the ‘top’ (i.e. Switzerland). The median value of years to reach the ‘top’ or

becoming ‘stable’ of these 15 countries also vary. The FSI predicts most daunting picture,

where the median years to become a ‘stable’ or ‘sustainable’ state is 365 and 611 years

respectively. In case of BTI and CIFP the median number of years to reach the respective

‘top’ ranking country is 185 and 198 years.

Table 3.4: Fragility Trap: 15 most fragile countries common in all four state fragility indices

Co

un

trie

s a

nd

Territ

orie

s

Resc

ale

d F

ra

gil

ity

Sco

re (

0-1

0 S

cale

)

Yrs

to R

ea

ch

'T

op

' (G

reen

lan

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ea

ch

Glo

ba

l A

vera

ge

Resc

ale

d F

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ity

Sco

re (

0-1

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)

Yrs

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ea

ch

To

p (

Sw

itzerla

nd

)

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rs

to R

ea

ch

Glo

ba

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verage

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d F

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ity

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re

( 0

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'T

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' (T

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an

)

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ea

ch

'G

lob

al

Av

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Resc

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Sco

re (

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)

Yrs

to S

tab

le(S

co

re 5

)

Yrs

to '

Su

sta

ina

ble

' (S

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re 7

.5)

SOMALIA 0.421 Infinity Infinity 1.488 Infinity Infinity 1.51 Infinity Infinity 0.500 5786 9000

SYRIA 0.525 3825 2198 3.000 184 76 1.77 1398 720 1.008 384 625

PAKISTAN 0.675 1949 1103 3.213 198 77 3.4 185 67 1.425 248 421

AFGHANISTAN 0.876 1510 837 2.438 590 277 3.135 321 127 1.008 689 1121

SUDAN 1.332 429 225 2.488 335 155 2.35 434 204 0.767 795 1265

CONGO, D.R. 1.283 425 224 2.388 351 166 2.97 209 86 0.858 559 896

IRAQ 1.686 417 208 3.438 206 75 4.065 147 40 1.292 365 611

CEN AFR. REP 1.424 358 185 2.288 402 194 3.725 120 38 0.675 1076 1698

YEMEN, REP. 1.085 246 133 2.713 103 46 3.8 51 16 0.992 180 293

MALI 2.191 180 82 2.738 238 105 4.14 92 24 2.242 84 159

MYANMAR 3.075 125 45 3.250 189 73 3.28 199 75 2.108 116 216

BURUNDI 2.837 113 44 2.913 195 83 4.41 76 16 1.825 121 216

CHAD 3.165 97 34 3.025 184 76 3.075 192 77 0.967 428 694

CÔTE

D'IVOIRE 3.248 93 32 3.263 152 59 4.47 76 15 1.667 149 261

MAURITANIA 3.305 90 30 3.550 124 43 4.22 88 22 2.092 96 179

Median Value

(Yrs)

358 185

198 77

185 67

365 611

According to FSI Bangladesh will take 117 years to become a ‘sustainable’ state and 60 years

to become a ‘stable’ state (see annex A). However, if the threshold is lowered to reaching the

global average, then Bangladesh will need 58 years (according to WGI), 13 years (according

to CIFP) and only 3 years (according to BTI). The negative values in case of some countries

reflect that these countries have already crossed the respective thresholds. For example

according to FSI, Singapore has crossed the ‘stable’ threshold in 1999 and the ‘global

average’ threshold in CIFP , in 1982 ( see annex A).


19

Table 3.3 and 3.4 provides a summary of annex A telling us how many countries will require

what duration to emerge from fragility in each index considering two different thresholds. It

reveals that over half of the countries (53.49%) listed in the FSI will require 50 years or more

to reach the lowest threshold of ‘sustainable’ status out of which 60 countries (33.52%) will

need 100 years or more to reach the same status and emerge out of fragility. However, if the

threshold is lowered to reaching the lowest threshold of ‘stable’ status, there are still 55

countries that will require 50 years or more to reach that status.

Table 3.5: Number of countries and ‘years to reach’ two different thresholds in four Indices

Number of Year Number of countries

reaching ‘Top’ /

‘Sustainable’ status

Number of countries reaching

Global Average/ ‘Stable’ status

BTI CIFP FSI WGI BTI CIFP FSI WGI

500 yrs or more 5 3 10 15 4 2 6 5

400 yrs or more 7 4 12 20 5 - 7 -

300 yrs or more 8 7 16 26 - - 10 -

200 yrs or more 11 13 33 35 6 3 13 8

150 yrs or more 21 27 47 44 - 6 17 11

100 yrs or more 35 51 60 58 8 8 30 19

50 yrs or more 68 94 95 93 14 21 55 26

The forward projection using CIFP fragility scores reveals that 94 countries (48.97%) will

require 50 years or more to reach the ‘top’ ranking country (Switzerland) and emerge out of

fragility out of which 51 countries (26.29%) will require 100 years or more to reach the same

status. However, if the threshold is lowered to reaching global average, there will still be 21

countries that will require more than 50 years to reach that level.

The BTI has the lowest coverage (129 countries) amongst all four indices. Based on BTI

scores, there are 68 countries (53.49%) that will require 50 years or more to reach Taiwan, the

0 20

40 60

80 100

BTI 2012

CIFP 2012

FSI 2015

WGI 2013

8.52

6.7

18.44

12.12

15.5

13.92

26.25

16.16

27.13

26.29

33.52

23.23

53.49

48.97

53.07

40.91

Figure 3.6: Cumulitive percentage of countries requiring 50 yrs or more

to reach 'Top'/'Suatainable' status in 4 fragility indices

200 yrs or more

151 yrs or more

100 yrs or more

50 yrs or more


20

‘top’ ranking country in that index and emerge out of fragility out of which 35 (27.13%)

countries will require 100 years or more to reach the same status. In case of a lower threshold

of reaching global average, there will still be 14 countries that will require 50 years or more

to reach the ‘global average’.

In case of WGI, the number of countries that will require 100 years or more to reach the ‘top’

(i.e. Greenland) is 46. The number increases to 81 countries in case the ‘years to reach top’

threshold is taken as 50 years and droops down to 26 countries in case the fragility score

threshold is lowered as reaching the ‘global average’ instead of the ‘top’ ranking country.

Be that as it may, it would be too naive to say that these are perfect estimates. Indeed, it is

biased towards states that are relatively new. It is evident both within and between the indices

having same fragility score but different ‘years since independence’ (see annex A). For

example, Turkey and India with almost similar fragility scores takes 394 and 191 years

respectively to reach the ‘top’ ranking country in WGI. Again, Pakistan and Venezuela with

similar fragility scores in WGI and CIFP takes different durations to come out of fragility

only because they became independent in different times. However, higher values of ‘years

since independence’ does not always imply greater fragility trap. For example, Switzerland

and Sweden which gained their statehood in 1816 consistently ranks in the top end of all four

indices and are located closer to the world’s economic and political ‘Centres’.

There are also problems with scaling as it does not tell us whether the difference between a

fragility score of 2 and 3 is same as a difference between a score of 6 and 7. Does it take

longer for a country to progress from 2 to 4 compared to 6 to 8 or vice versa? The underlying

process of progress out of fragility may not be liner; countries could have reached some ‘take

off’ points or a ‘tipping point’ from where they can achieve either accelerated progress or

spiral into more fragility. This essentially relates to the question as to what constitutes

‘necessary’ and ‘sufficient’ conditions for fragility. Is a stable external security environment a

sufficient or necessary condition for countries to come out of fragility? How much does the

presence or absence of a favourable security environment contribute towards the ‘take off’ or

‘tipping off’ point for a country? Why did the newly independent countries in Europe

following the demise of the former Soviet Union were able to better consolidate their state-

building in a shorter period of time compared to the African countries?


21

Identifying the ‘necessary’ and ‘sufficient’ conditions is also essential from a methodological

point of view. If a favourable security environment is considered as a ‘necessary’ condition

to come out of fragility, then adding the mean of aggregation of security dimension with

others (such as the scores in economic, political, social, environmental dimensions) would be

misleading as the other dimension could partly compensate for a lack of security and lift the

country over the threshold of fragility. A more valid method would be to multiply the other

dimensions with security. The score will then always be zero when security is zero and thus

satisfy the conceptual assumption as a ‘necessary’ condition.

Despite such limitations, collectively what these arithmetic illustrations tells us is: within the

conceptual boundary of each index, a large number of states will require hundreds of years to

come out of fragility if they continue to maintain their long run trajectories. It confirms the

existence of ‘fragility trap’. Such findings stand as a sharp contrast to the reality. In reality,

we see countries like South Korea - one of the major aid recipient nations and the poorest

countries in 1950’s, emerged as a donor nation and the 12th largest economy in the world in

about 40 years – much less than the periods derived through the data of four fragility indices.

In sum, the revelation of fragility trap leaves us with two choices regarding the fragile state

problematique. One is to view these narratives as a ‘political constructions’ and reject or

relegate them as a mere ‘expression of power’. Indeed many scholars have taken this path

suggesting that the 'ranking' produced by these indexes need to be understood as narrative

constructs which, to borrow from Robert Cox, are ‘always for someone and for some

purpose’. The other choice is to offer a better framework of analysis to understand and

investigate this ‘real world’ problem of state fragility. We subscribe to the second choice.

IV. STATE FRAGILITY THROUGH THE CENTRE-PERIPHERY FRAMEWORK

The Centre and Periphery Model

Notwithstanding the scepticism, the Centre-Periphery framework22

provides a good analytic

tool to examine the global-local interactions to better understand and explain state fragility

22

The Centre - Periphery framework and its deviants have been used by many scholars to explain the

global-local interactions. See Frank, A. G., (1966: 16-20), The Development of Underdevelopment,

Monthly Review September and Johan Galtung (1969: 167-191, 171), 'Violence, Peace, and Peace

Research', Journal of Peace Research, vol. 6 no. 3. For the criticism of the model see Boulding, KE

(1977;75-86) ‘Twelve Friendly Quarrels with Johan Galtung’ in Journal of Peace Research, Vol. 14,

1; and Nancy Scheper-Hughes (2004: 14-18)., Death Without Weeping: The Violence of Everyday Life


22

(See figure 4.1). The model presupposes that fragility is concentrated mostly in the Peripheral

states. It takes into account two levels of interaction that are mutually inclusive. First, at the

external level it presupposes that the centre of the Centre (CC) and the centre of the Peripheral

states (PC) are coupled through an interaction structure to facilitate economic, political, social,

security interaction between the two. Exploring the nature and interaction structure may allow

us to explain the causality of state fragility in the Peripheral states. Interaction between the

parties is essential for this model to work; mutually isolated parties may not qualify to

demonstrate a conflictual or harmonious interaction. Second, at the domestic level each state

has its centre(s) (i.e. capital, major cities from where the governmental machineries work)

and their respective peripheries. The interaction between Cc and Pc with their respective

peripheries (i.e. Cp and PP) could explain the ‘intra’ level causality of state fragility specific to

that context. Thus the model allows both historicizing and contextualizing the fragile state

problematique. Indeed the ‘inter’ and ‘intra’ level interactions between and within the states

cannot be viewed in isolation as they both contribute towards avoiding state fragility

particularly in Peripheral states.

Figure 4.1 Framework of analysis: Centre –Periphery model

The Nature of Centre-Periphery Interaction

At the very basic level, the nature of interaction between (inter) and within (intra) the Centre

and Peripheral state could be characterized as either harmonious or conflictual. At the global

level a harmonious interaction could result in building alliance providing security guarantee,

full access to its markets, preferential trade arrangements etc insulating and protecting the

Peripheral state from unforeseen security and economic threats. When such arrangements are

truly non-intrusive, unconditional and egalitarian in nature, they may greatly contribute

in Brazil, University of California Press. Also see Wallerstein (1979), The Capitalist World-Economy

where he argues that the international order is premised on an exploitative hierarchy with a developed

core, semi-periphery and underdeveloped periphery.


23

towards the progress of a Peripheral state. In such conditions, the ideals of globalization are

truly realized creating a favourable condition for the development and progress of all states.

However, in reality the nature of interactions between the Centre and the Periphery is often

conflictual as they are shaped by interest and priorities. Thus we find a rapid increase in

export of small arms and weapons fuelling the ‘new wars’,23

a protectionist and unfair trade

practice such as farm subsidies (in USA) or Common Agricultural Policy (in EU), ‘currency

wars’, 24

climate change challenges etc rooted in the actions of the states in the Centre. The

second and third order impact of such conflictual interaction adversely impacts the security,

productive capacity, growth and the overall living conditions in the peripheral states where

majority of the humanity lives. For example, the unconventional monitory policy pursued by

the Federal Reserve of the USA and the so called ‘taper tantrum’ resulted a capital outflow of

over $548 billion from the emerging markets in 2015 alone (largest outflow since 1988)

chocking the much needed investment for infrastructural development in the Peripheral

states.25

Thus a conflictual interaction between the Cc and Pc creates, what Pope Francis

dubbed a ‘globalization of indifference’.

Similarly, the nature of ‘intra’ level interaction between the Centres and the respective

peripheries may be harmonious or conflictual. At the ‘intra’ level the government at the

centre seeks to control its territory and harness its resources, promulgates and implements

policies that may or may not be justified and equitable for the periphery. The prudence (or the

lack of it) with which the Centres regulate policies and take care of their respective

peripheries in the domestic front is a key determinant of state fragility. Indeed, most fragility

definitions capture this discrepancy and distributive injustice between the centre and the

23

For an enlightening discussion and facts on global trend in arms export see Pieter D. Wezeman and

Siemon T. Wezeman (2015), Trend in International Arms Transfers - 2014, SIPRI Fact Sheet, March

2015, and Andrew T. H. Tan ed. (2010: 3-10) The Global Arms Trade: A Handbook, Taylor and

Francis, New York. For the effects of global arms trade in Africa see Matt Schroeder and Guy Lamb

(2006:69-78) ‘‘The Illicit Arms Trade in Africa, A global Enterprise’’, African Analyst, Third

Quarter. For the success and failure of the global efforts for conventional arms control see Sibylle

Bauer ‘‘Post- Cold war Control of Conventional Arms’’, in Andrew T. H. Tan ed. (2010: 306 -312). 24

The main instrument for currency war is the monitory policy. Monetary policies adopted by

advanced economies, in particular the US, have contributed to the dramatic weakening of emerging-

market currencies. See Dambisa Moyo (2015) ‘The Global Migration Blowback’, Project Syndicate,

The World Opinion Page. Available at: www.project-syndicate.org/ 25

For details of ‘taper tantrum’ see Ratna Sahay, Vivek Arora, Thanos Arvanitis, Hamid Faruqee,

Papa N'Diaye, Tommaso Mancini-Griffoli, and an IMF Team (2014:16-24) Emerging Market

Volatility: Lessons from the Taper Tantrum, IMF Staff Discussion Note, SDN14/09, September 2014.

Also see Dan McCrum (2015), ‘EM at the mercy of shifting money flows’, Financial Times, October

5, 2015. Available at: http://www.ft.com/ (Accessed 18 December 2015).

http://www.project-syndicate.org/

http://www.ft.com/


24

periphery. For example the DFID’s definition of fragile state: ‘‘government is not willing or

capable of providing core services to most of its populations particularly to the poor’’ is

premised on the distributive injustice by the centres of Peripheral states.

However, the ability of Peripheral states to be ‘willing and capable’ to provide the political

good to its entire citizen is much harder if it has a conflictual interaction at the global level.

Conversely a harmonious relationship at the global level pays rich dividend. The density of

connectivity with other states in terms of coalitions, alliances, trade etc together with the

prudent policies, instruments and roadmaps is crucial to offset or insulate the the Peripheral

state from the regressive global impact. Such a mutually inclusive nature of interactions

within and between the Centre and Peripheral states could be of four different variants

generating four different hypothesis that can help explain the propensity of state fragility (see

table 4.2).

Table 4.2: Propensity of state fragility

Interaction between Nature of Interactions

centre of Centre and centre

of Periphery States

(Cc and Pc )

Harmonious Conflictual Harmonious Conflictual

centres of the Centre and

Periphery States with their

respective peripheries (Cc & Pc with Cp and PP)

Justified

and

Equitable

Unjustified and

Unequal

Unjustified

and Unequal

Justified and

Equitable

Propensity of Fragility No

Fragility

Very High

Medium/high

Medium/high

H1: If the interaction between the Cc and Pc is harmonious and the interaction between

Cc and Pc with their respective peripheries (i.e. Cp and PP) is based on justified and

equitable policy practices it is unlikely for the state to have any fragility.

H2: When the interaction between Cc and Pc is conflictual and policy practice by the

Cc and Pc towards their respective Cp and PP is unjustified and unequal the propensity

of fragility is likely to be very high.

H3: If the interaction between the Cc and Pc is harmonious, but the policy practice by

the Cc and Pc towards their respective Cp and PP is unjustified and unequal we may see

medium or high level of fragility.


25

H4: If the interaction between Cc and Pc is conflictual but the policy practice by the Cc

and Pc towards their respective Cp and PP is well justified and equitable in nature, the

state may show a medium or high level of fragility.

Hypothesis 1(H1) reflects the most ideal condition where all external and internal factors are

geared towards complementing each other for the progress and development of the people

and the state resulting in no fragility. In such condition (H1), the global forces play a

progressive role and are sustained by an equally prudent and justified domestic structure and

policies resulting in the state’s ability to dispense positive political goods to its citizens. The

economic, social, political and security exchange between the CC and the Pc tends to benefit

both parties which are subsequently transmitted/distributed by the Centres to their respective

peripheries resulting in a positive intra-actor effects. As a result, is unlikely for the peripheral

states to succumb to fragility. Welfare states resembles such a condition where the dividend

of progressive global forces is effectively harnessed by a prudent and well structured social

welfare system to serve the political good to all its citizens.

The conditions in H2 reflect the opposite of H1; here the external dimension is conflictual and

the internal interaction between the respective centres and peripheries are also unjustified and

unequal creating a condition of high propensity of fragility. The global factors play a

regressive role in this situation and are often multiplied or transformed by the unjustified and

unequal local conditions reproducing state weakness. The regressive global forces in such

conditions may work through multiple channels. For example, the external forces may work

as a catalyst to heighten the security dilemma of the peripheral state, fragment the state-

society relations by identity restructuring, attract conflict entrepreneurs to fuel or sustain civil

wars or internal conflict, facilitate natural resource predation, derail the prospect of economic

emancipation due to abrupt and unplanned liberalization etc. All of these result in

constraining the state to provide the positive political good to its citizens in the long run and

make them fragile, failed or even collapsed state.

However, most Peripheral states straddle in the middle similar to the conditions as described

in H3 and H4. These scenarios are not straight-forward and may depend on many associated

factors like degree of integration with the international structure, strategic significance,

resourcefulness, demography, remoteness etc. However, in both cases, some degree of

fragility is inevitable. In case of H3, the benefits of the progressive global forces are limited


26

to the PC as the state pursues an unequal and unjustified policy practices towards its

peripheries. In such conditions the external engagements are often used by the political elites

to prolong their stay in power and strengthen ‘regime security’ instead of national security.

Coercion is often preferred over consent as the regime in the centre of the peripheral state

mostly draws its support and legitimacy from outside. Such condition is particularly

sustainable where the Peripheral state is endowed with rich mineral resources and the value

exchange from these resources can free the government from raising tax from its own people.

As a result, it creates a parasitic domestic elites sustaining on external support whose primary

aim is to protect their own power base and maximize their wealth with no particular regards

to the people in the periphery. The penetration of progressive global forces into the PP is

fiercely checked by the government in the PC by coercive means, censorship, banning social

media, internet etc.

In case of H4, the ‘intra’ level structures and policies are justified and equitable as the

government in the PC aims to dispense positive political goods to all its citizens in the face of

a conflictual ‘inter’ actor relationship. Such conflictual interaction between the Cc and Pc

may be due to historical, political, economic or security reasons restricting the Peripheral

state to become resilient. For example, a hostile or less favourable external environment may

compel the state to increase its defence budget to maintain internal order or repel any external

attack at the expense of socio-economic development. Similarly economic remoteness – i.e.

distance of the country from its major trading partners may put undue strain on the economy

in general and commodity price in particular. The H4 scenario can also explain the demand-

driven state fragility attributed to the demographic pressure: High population growth can

strain states’ capacity to maintain order, provide education, health services, housing etc.

However, more population can also increase state’s coffer in tax receipt; but that only

happens if the economy is growing – which, in a conflictual ‘inter’ actor relationship is

difficult even with sound domestic policy. Indeed as Gros (2013: 556) succinctly puts:

‘‘autarky is the enemy of any state or political economy based on trade.’’ Peripheral state

may try to minimize the effects of regressive global forces and strive for self sufficiency and

economic independence but a conflictual interaction with the Centre often puts a limit to such

struggle to emerge from fragility.


27

V. CONCLUDING REMARKS

Conceptualizing state only as a ‘functional entity’ and devoid of any history, power relations

and fluidity in composition can largely obscure our understanding on state fragility. States’

power and propensity to resist or succumb to fragility is embedded within the causal

complexes comprising both internal and external conditions. States as a political entity aim to

achieve control over its territory and harness its resources-- including human resources. In the

process of pursuing this aim, states face both ‘intra’ and ‘inter’ level challenges that may be at

the structural and agency level. The internal structural challenges could be geographic,

demographic, economic, class, ethnicity, elite bargain etc. Chief among the external structural

constraints are the security dilemma, unequal terms of trade and exchange, adverse

international market conditions, remoteness, environmental factors etc. The internal and

external challenges are mutually inclusive, contextual and dynamic in nature. Thus a land

lock country or a country with a high percentage of population in the low elevated coastal

zones faces different economic or environmental challenges compared to the opposite.

The current quantitative methods used in different state fragility indices to measure state

weakness mirrors methodological individualism where the performance of state is atomized

into its domestic functionalities. States are treated as ‘given’ or ‘primitive’ units with little or

no regards to the externalities in which they are embedded. Such reductionist

conceptualization restricts the explanatory leverage of taking into account the effects of

externalities. As a result of such ‘thin’ conceptualization, many fragility indices points to a

trajectory for the fragile states towards a fragility trap – a condition of state stagnation. Such

inadequacies in the state fragility indices can be addressed by sufficiently including the

external drivers of fragility using the Centre – Periphery model. The model also allows

contextualizing and historicizing state fragility while emphasizing the need of an enabling

external environment for the Peripherals states to emerge out of fragility.

A Peripheral state does not necessarily seek to control the external environment but minimize

the adverse impact while its strategy for achieving control for internal environment is often a

mixture of coercion and consent. The interests and priorities of the external actors often shape

and influence the direction of the policy practice by the political elites of the Peripheral states.

Indeed as we see external players compelled a democratically elected government in Greece

to succumb to harsher austerity plans, an ultimatum by the USA to ‘be prepared to go back to

the Stone Age’ compelled Pakistan to join the Global War on Terrorism that has greatly


28

contributed towards its fragility. Such external ‘realities’ underscore the need for finding

solutions to global issues that are synced and harmonious to internal conditions.

Articulating solutions of the regressive global forces also hinges on the capacity of the

international system. Indeed, fighting state fragility relates as much to enhancing the capacity

of the international system as it is to the capacity of individual nations. An international

system that can prevent or reduce the incentives for the countries to undertake action that are

conflictual, uncooperative and inward-looking may help in creating conditions that would

allow development of all nations. This can only happen when there is a harmony in the goals

and interest. Indeed, a convergence of interests and goals between the developed ‘Centre’ and

the ‘Peripheral’ fragile states is essential to decrease the ‘gap’ and effectively address the

problem of state fragility. Failing to do that would make the phenomenon of fragile states a

rather inevitable feature of the international system.

(Words: 11,375)


29

Annex A: Fragility Trap – Number of years required by each county to reach ‘Top/Sustainable’ and ‘Stable/Global Average’ threshold

3. WGI 2013 - PS & AV CIFP 2012 5. BTI 2014 6.FSI 2015

1.

Co

un

trie

s a

nd

Terri

torie

s

2.

Yr o

f In

dep

en

den

ce

3.1

Resc

ale

d F

rag

ilit

y S

core

on

0-1

0 S

cale

3.2

Op

tim

isti

c A

nn

ua

l P

ace

of

Pro

gress

3.3

Yrs

to R

each

'T

op

' (G

ree

nla

nd

)

3.4

Yrs

to R

each

Glo

ba

l A

vera

ge

4.1

Resc

ale

d F

rag

ilit

y S

core

on

0-1

0 S

cale

4.2

Op

tim

isti

c P

ace o

f P

rogress

4.3

Yrs

to R

each

To

p (

Sw

itzer

lan

d)

4.4

Yea

rs

to R

each

Glo

ba

l A

vera

ge

5.1

Resc

ale

d F

rag

ilit

y S

core

on

0-1

0 S

cale

5.2

Op

tim

isti

c A

nn

ua

l P

ace

of

Pro

gress

5.3

Yrs

to R

each

'T

op

' (T

aiw

an

)

5.4

Yrs

to R

each

'G

lob

al

Av

era

ge'

6.1

Resc

ale

d F

rag

ilit

y S

core

on

0-1

0 S

cale

6.2

Op

t P

ace o

f P

rog

ress

6.3

Yrs

to S

tab

le(S

core

5)

6.4

Yrs

to '

Su

stain

ab

le'

(Sco

re 7

.5)

AFGHANISTAN 1919 0.876 0.005 1510 837 2.437 0.01 590 277 3.135 0.017 321 127 1.008 0.006 689 1121

ALBANIA 1944 5.097 0.068 46 -2 5.575 0.06 48 -5 5.86 0.062 45 -9 4.842 0.063 3 42

ALGERIA 1962 3.050 0.052 100 36 4.212 0.055 78 19 4.845 0.064 59 7 3.367 0.056 29 74

ANGOLA 1975 4.380 0.104 37 5 4.162 0.072 59 15 4.215 0.069 64 16 2.658 0.056 42 86

ANTIGUA AND

BARBUDA 1981 6.630 0.194 8 -9 5.8 0.139 19 -4 5.183 0.143 -1 16

ARGENTINA 1841 5.100 0.027 114 -6 6.25 0.028 79 -35 5.875 0.025 109 -23 6.033 0.032 -32 46

ARMENIA 1991 5.117 0.213 14 -1 5.675 0.199 14 -2 5.275 0.164 20 0 4.192 0.162 5 20

AUSTRALIA 1920 6.694 0.067 22 -26 7.55 0.066 14 -35 7.975 0.080 -37 -6

AUSTRIA 1955 7.238 0.118 8 -20 8.113 0.116 3 -25 7.833 0.125 -23 -3

AZERBAIJAN 1991 4.316 0.177 22 3 5.225 0.178 18 0 4.33 0.123 35 8 3.558 0.135 11 29

BAHAMAS, THE 1973 6.868 0.161 8 -12 6.213 0.121 19 -8 5.700 0.128 -5 14

BAHRAIN 1971 2.763 0.056 97 39 4.788 0.08 46 6 4.65 0.073 55 9 4.642 0.097 4 29

BANGLADESH 1971 2.312 0.045 131 58 4.338 0.07 59 13 5.04 0.082 44 3 2.350 0.044 60 117

BARBADOS 1966 7.155 0.143 7 -16 6.575 0.111 17 -12 5.892 0.113 -8 14

BELARUS 1991 4.958 0.206 16 0 5.213 0.177 18 0 3.53 0.088 58 20 3.700 0.141 9 27

BELGIUM 1945 6.529 0.090 18 -18 7.363 0.088 13 -24 7.467 0.102 -24 0


30

1. 2 3.1 3.2 3.3 3.4 4.1 4.2 4.3 4.4 5.1 5.2 5.3 5.4 6.1 6.2 6.3 6.4

BELIZE 1981 5.289 0.152 19 -2 5.313 0.123 26 0 4.558 0.124 4 24

BENIN 1960 5.467 0.095 29 -6 4.038 0.049 90 25 6.2 0.087 28 -10 3.433 0.055 28 74

BHUTAN 1971 6.333 0.141 13 -10 4.75 0.08 47 6 5.97 0.104 26 -6 3.442 0.069 22 58

BOLIVIA 1848 4.421 0.024 155 21 4.95 0.021 166 15 5.92 0.027 102 -23 3.500 0.018 82 218

BOSNIA AND

HERZEGOVINA 1992 4.390 0.189 20 3 5.1125 0.181 18 1 5.16 0.166 21 1 3.550 0.141 10 28

BOTSWANA 1966 6.761 0.135 11 -14 5.675 0.091 31 -5 7.415 0.123 10 -17 4.767 0.090 3 30

BRAZIL 1822 4.536 0.022 170 18 5.8625 0.023 113 -26 7.66 0.032 30 -74 4.783 0.023 10 121

BRUNEI DARUSSALAM 1984 6.804 0.220 6 -9 5.7125 0.151 18 -3 4.750 0.143 2 19

BULGARIA 1908 5.293 0.046 62 -8 6.2375 0.046 49 -21 7.22 0.054 26 -36 5.383 0.046 -8 46

BURKINA FASO 1960 3.745 0.063 71 19 4.1125 0.05 86 23 5.165 0.068 51 2 2.567 0.039 62 126

BURUNDI 1962 2.837 0.047 113 44 2.9125 0.029 195 83 4.41 0.056 76 16 1.825 0.026 121 216

CAMBODIA 1953 4.741 0.072 48 3 4.5 0.051 78 15 3.815 0.038 127 39 2.675 0.036 64 133

CAMEROON 1960 4.137 0.070 58 11 3.9 0.046 98 29 3.89 0.044 108 32 2.142 0.031 92 172

CANADA 1920 6.718 0.068 22 -26 7.5375 0.066 14 -35 7.858 0.079 -36 -5

CAPE VERDE 1975 6.344 0.156 12 -9 5.125 0.098 34 1 3.875 0.088 13 41

CENTRAL AFRICAN

REPUBLIC 1960 1.424 0.019 358 185 2.2875 0.015 402 194 3.725 0.041 120 38 0.675 0.004 1076 1698

CHAD 1960 3.165 0.052 97 34 3.025 0.03 184 76 3.075 0.029 192 77 0.967 0.009 428 694

CHILE 1839 5.622 0.030 86 -23 6.8875 0.031 50 -52 8.02 0.037 16 -73 6.542 0.035 -44 28

CHINA 1860 4.090 0.024 171 35 5.1 0.024 142 7 4.975 0.023 162 14 3.633 0.021 66 188

COLOMBIA 1831 2.886 0.014 392 151 5.0375 0.02 175 12 6.22 0.026 94 -36 3.125 0.015 129 300

COMOROS 1975 4.602 0.110 33 3 3.825 0.063 73 23 3.058 0.067 29 67

CONGO, DEM. REP. 1960 1.283 0.016 425 224 2.3875 0.017 351 166 2.97 0.027 209 86 0.858 0.007 559 896

CONGO, REP. 1960 4.223 0.072 55 10 3.725 0.043 110 36 3.725 0.041 120 38 2.433 0.037 70 139

COSTA RICA 1920 6.110 0.061 34 -19 6.6 0.056 34 -24 7.75 0.066 13 -37 6.108 0.060 -18 23

CÔTE D'IVOIRE 1960 3.248 0.053 93 32 3.2625 0.034 152 59 4.47 0.055 76 15 1.667 0.022 149 261

CROATIA 1992 6.023 0.267 8 -4 6.9125 0.271 6 -6 7.315 0.264 5 -8 5.750 0.241 -3 7

CUBA 1909 5.616 0.050 52 -14 5.8875 0.043 60 -15 3.89 0.023 209 62 4.383 0.037 16 83


31

1. 2 3.1 3.2 3.3 3.4 4.1 4.2 4.3 4.4 5.1 5.2 5.3 5.4 6.1 6.2 6.3 6.4

CYPRUS 1960 5.864 0.103 23 -9 6.675 0.1 18 -14 4.483 0.075 7 40

CZECH REPUBLIC 1993 6.754 0.317 5 -6 7.125 0.297 5 -6 8.04 0.311 2 -9 6.883 0.306 -6 2

DENMARK 1945 6.578 0.091 18 -18 8.4 0.103 1 -30 8.208 0.112 -29 -6

DJIBOUTI 1977 4.802 0.122 28 1 3.85 0.068 68 21 2.658 0.059 39 81

DOMINICAN REPUBLIC 1924 5.311 0.055 52 -7 5.275 0.043 74 0 5.88 0.049 57 -12 4.067 0.040 23 86

ECUADOR 1854 4.674 0.027 131 10 5.1 0.023 147 7 5.085 0.022 159 10 3.675 0.020 66 190

EGYPT, ARAB REP. 1937 2.300 0.025 238 106 4.5375 0.041 97 18 4.79 0.043 90 12 2.500 0.027 94 189

EL SALVADOR 1875 4.927 0.033 100 0 5.4875 0.029 102 -8 7.035 0.040 40 -44 4.050 0.026 37 134

EQUATORIAL GUINEA 1968 5.135 0.105 29 -2 3.625 0.049 100 34 2.933 0.054 38 85

ERITREA 1993 3.707 0.164 27 7 3.325 0.097 53 20 1.55 0.002 3717 1969 1.925 0.070 44 80

ESTONIA 1991 6.209 0.263 8 -5 6.975 0.261 6 -7 8.34 0.297 1 -10 6.350 0.256 -5 4

ETHIOPIA 1941 2.676 0.031 176 72 3.1 0.023 236 95 3.95 0.033 140 40 1.875 0.019 161 290

FIJI 1970 4.956 0.105 31 0 4.8 0.079 46 6 3.600 0.071 20 55

FINLAND 1917 7.265 0.071 13 -33 7.9 0.068 8 -39 8.517 0.083 -42 -12

FRANCE 1944 5.706 0.077 32 -10 7.3625 0.086 13 -24 7.192 0.096 -23 3

GABON 1960 5.562 0.097 27 -7 4.675 0.061 62 10 4.058 0.067 14 52

GAMBIA, THE 1965 4.923 0.094 35 0 3.4 0.041 124 46 2.883 0.049 43 93

GEORGIA 1991 4.227 0.173 23 4 5.575 0.195 15 -2 5.97 0.194 14 -3 3.392 0.128 13 32

GERMANY 1990 6.545 0.266 6 -6 7.9875 0.295 2 -9 7.658 0.300 -9 -1

GHANA 1957 5.034 0.082 38 -1 5.175 0.067 49 1 7 0.096 17 -18 4.008 0.062 16 56

GREECE 1944 4.671 0.062 57 4 6.7 0.077 23 -19 5.617 0.074 -8 26

GREENLAND 1979 8.190 0.229 0 -14

GRENADA 1974 5.697 0.135 18 -6 6.5 0.132 15 -9 4.717 0.106 3 26

GUATEMALA 1868 3.842 0.024 184 46 4.5125 0.021 188 36 4.995 0.024 152 13 3.300 0.019 87 216

GUINEA 1958 2.957 0.046 113 43 3.1 0.03 180 72 4.895 0.060 62 7 1.258 0.014 262 437

GUINEA-BISSAU 1974 3.446 0.078 61 19 2.6 0.025 232 105 1.675 0.026 126 220

GUYANA 1966 4.264 0.082 48 8 4.575 0.067 58 10 4.125 0.076 11 44

HAITI 1934 3.895 0.044 98 24 3.6625 0.028 172 57 3.555 0.026 199 68 1.292 0.010 356 596


32

1. 2 3.1 3.2 3.3 3.4 4.1 4.2 4.3 4.4 5.1 5.2 5.3 5.4 6.1 6.2 6.3 6.4

HONDURAS 1899 4.223 0.033 119 21 4.625 0.028 138 23 5.735 0.037 79 -12 3.483 0.026 58 153

HUNGARY 1918 6.299 0.062 31 -22 6.788 0.056 30 -27 6.505 0.052 41 -23 5.908 0.057 -16 28

ICELAND 1944 7.100 0.097 11 -22 7.575 0.09 10 -26 8.050 0.108 -28 -5

INDIA 1947 3.021 0.039 131 48 4.288 0.043 97 23 6.755 0.078 24 -19 3.383 0.044 37 94

INDONESIA 1949 4.166 0.059 69 13 4.9 0.054 66 7 6.235 0.073 33 -13 3.750 0.051 25 74

IRAN, ISLAMIC REP. 1855 2.885 0.016 340 131 3.875 0.015 302 91 2.495 0.006 990 453 2.733 0.014 158 333

IRAQ 1932 1.686 0.016 417 208 3.438 0.024 206 75 4.065 0.031 147 40 1.292 0.010 365 611

IRELAND 1922 6.463 0.066 26 -23 7.663 0.069 12 -35 7.942 0.081 -36 -5

ISRAEL 1948 3.177 0.042 118 41 6.05 0.071 34 -11 3.383 0.044 36 93

ITALY 1816 5.850 0.028 85 -33 7.163 0.029 45 -66 6.400 0.030 -47 37

JAMAICA 1962 5.294 0.096 30 -4 5.3 0.076 41 0 6.385 0.094 24 -12 4.617 0.080 5 36

JAPAN 1952 6.636 0.102 15 -17 7.8 0.105 6 -24 7.000 0.106 -19 5

JORDAN 1946 3.973 0.053 80 18 4.838 0.051 71 8 4.87 0.049 76 9 3.592 0.046 31 85

KAZAKHSTAN 1991 4.364 0.179 21 3 5.363 0.185 17 -1 4.86 0.146 26 3 4.308 0.167 4 19

KENYA 1963 3.086 0.053 96 35 3.588 0.043 114 39 5.325 0.075 44 0 1.883 0.028 112 201

KOREA, DEM. REP. 1948 4.116 0.057 72 14 4.6 0.049 79 14 1.68 0.003 2698 1406 2.183 0.026 108 203

KOREA, REP. 1949 5.394 0.078 36 -6 7.288 0.092 13 -22 7.79 0.097 9 -26 6.975 0.100 -20 5

KOSOVO 2008 3.359 0.588 8 3 4.275 0.697 6 1 5.715 0.701 4 -1

KUWAIT 1961 5.237 0.093 32 -3 5.35 0.076 41 -1 5.125 0.068 51 3 5.208 0.090 -2 26

KYRGYZ REPUBLIC 1991 3.483 0.139 34 10 4.4 0.139 29 6 5.15 0.158 22 1 3.150 0.117 16 37

LAO PDR 1953 5.108 0.078 39 -2 4.075 0.044 100 27 3.895 0.039 121 36 2.958 0.041 50 111

LATVIA 1991 5.954 0.252 9 -4 7 0.263 6 -7 7.615 0.265 4 -9 5.950 0.239 -4 6

LEBANON 1946 2.175 0.026 230 105 4.725 0.049 76 11 4.96 0.051 72 7 2.658 0.032 72 150

LESOTHO 1966 5.544 0.109 24 -6 4.625 0.068 56 9 5.24 0.078 44 1 3.342 0.060 28 69

LIBERIA 1920 4.231 0.041 97 17 3.363 0.02 250 93 5.86 0.046 60 -12 1.892 0.015 204 368

LIBYA 1951 1.984 0.025 246 117 4.225 0.045 94 23 4.36 0.045 94 21 2.058 0.025 116 214

LITHUANIA 1991 6.537 0.278 6 -6 7.45 0.284 4 -8 8.03 0.283 2 -10 6.417 0.259 -5 4

LUXEMBOURG 1944 7.220 0.099 10 -23 7.5 0.088 11 -25 8.150 0.110 -29 -6


33

1

2 3.1 3.2 3.3 3.4 4.1 4.2 4.3 4.4 5.1 5.2 5.3 5.4 6.1 6.2 6.3 6.4

MACEDONIA, FYR 1993 4.377 0.198 19 3 5.463 0.209 14 -1 6.645 0.245 8 -5 4.625 0.198 2 14

MADAGASCAR 1960 3.809 0.064 69 18 3.65 0.042 116 39 3.94 0.045 104 30 3.033 0.048 41 94

MALAWI 1964 4.626 0.086 42 4 3.975 0.052 87 25 5.89 0.088 31 -7 2.758 0.046 49 103

MALAYSIA 1957 5.086 0.083 37 -2 5.95 0.081 31 -8 5.99 0.079 34 -9 4.508 0.071 7 42

MALDIVES 1965 5.237 0.100 29 -3 4.8 0.07 52 7 3.817 0.069 17 54

MALI 1960 2.191 0.033 180 82 2.738 0.024 238 105 4.14 0.049 92 24 2.242 0.033 84 159

MALTA 1964 6.678 0.128 12 -14 7.238 0.12 10 -16 6.592 0.123 -13 7

MAURITANIA 1960 3.305 0.054 90 30 3.55 0.04 124 43 4.22 0.050 88 22 2.092 0.030 96 179

MAURITIUS 1968 6.560 0.136 12 -12 6.45 0.113 18 -11 7.35 0.127 10 -16 6.233 0.126 -10 10

MEXICO 1831 3.771 0.018 240 63 5.763 0.024 114 -21 6.23 0.026 93 -36 4.017 0.019 51 179

MICRONESIA, FED. STS. 1991 6.851 0.292 5 -7 4.875 0.161 22 2 3.867 0.148 8 25

MOLDOVA 1991 4.944 0.206 16 0 5.688 0.2 14 -2 5.925 0.192 14 -3 3.917 0.150 7 24

MONGOLIA 1921 5.832 0.059 40 -15 5.338 0.042 74 -2 6.365 0.052 43 -20 5.250 0.052 -5 44

MONTENEGRO 2006 5.808 0.770 3 -1 5.275 0.631 5 0 6.96 0.681 2 -2 5.483 0.628 -1 3

MOROCCO 1956 4.167 0.066 61 12 5.325 0.069 46 -1 4.53 0.052 79 15 3.783 0.057 21 65

MOZAMBIQUE 1975 4.548 0.109 34 4 3.8 0.062 75 23 5.43 0.101 32 -1 2.758 0.059 38 80

MYANMAR 1948 3.075 0.041 125 45 3.25 0.028 189 73 3.28 0.027 199 75 2.108 0.025 116 216

NAMIBIA 1990 6.549 0.266 6 -6 5.363 0.176 18 -1 6.655 0.214 9 -6 4.100 0.152 6 22

NEPAL 1920 3.098 0.029 177 64 4.138 0.029 150 39 4.175 0.028 157 40 2.458 0.021 119 237

NETHERLANDS 1945 6.862 0.095 14 -20 8.1 0.099 4 -29 7.767 0.106 -26 -3

NEW ZEALAND 1920 7.416 0.075 10 -33 7.75 0.068 10 -37 8.117 0.081 -38 -8

NICARAGUA 1900 4.588 0.037 98 9 4.588 0.028 140 24 5.205 0.032 106 3 3.417 0.026 61 157

NIGER 1960 2.839 0.046 117 46 3.538 0.039 125 44 5.715 0.078 37 -5 1.850 0.026 122 219

NIGERIA 1960 1.534 0.021 317 162 3.4 0.037 138 51 4.985 0.064 57 5 1.467 0.019 189 323

NORWAY 1945 7.219 0.100 10 -23 8.2 0.1 3 -29 8.267 0.113 -29 -7

OMAN 1971 5.794 0.128 19 -7 4.9 0.083 43 4 4.34 0.066 65 15 5.667 0.121 -6 15

PAKISTAN 1947 0.675 0.004 1949 1103 3.213 0.027 198 77 3.4 0.028 185 67 1.425 0.014 248 421


34

1 2 3.1 3.2 3.3 3.4 4.1 4.2 4.3 4.4 5.1 5.2 5.3 5.4 6.1 6.2 6.3 6.4

PANAMA 1903 4.777 0.040 86 4 5.8 0.04 67 -14 6.235 0.043 56 -22 5.450 0.045 -10 46

PAPUA NEW GUINEA 1975 4.126 0.097 42 8 4.675 0.086 44 7 5.15 0.093 37 2 3.050 0.066 29 67

PARAGUAY 1876 3.883 0.025 170 41 5.063 0.026 129 8 5.94 0.032 84 -20 4.058 0.026 36 132

PERU 1839 3.713 0.019 237 64 5.6 0.024 120 -14 6.49 0.028 75 -42 4.008 0.020 49 172

PHILIPPINES 1946 3.234 0.042 118 40 4.888 0.052 69 7 6.035 0.067 39 -11 2.808 0.035 63 136

POLAND 1945 6.579 0.091 18 -18 7.225 0.086 14 -23 8.185 0.097 5 -30 6.683 0.090 -19 9

PORTUGAL 1816 6.234 0.030 66 -44 7.413 0.03 35 -71 7.525 0.036 -71 -1

QATAR 1971 7.029 0.157 7 -13 5.913 0.108 24 -6 6.095 0.107 24 -7 6.142 0.132 -9 10

ROMANIA 1878 5.255 0.036 82 -9 6.4 0.037 56 -31 6.85 0.039 45 -39 5.483 0.037 -13 55

RUSSIAN FEDERATION 1816 3.749 0.017 263 70 4.813 0.017 215 27 4.57 0.015 263 47 3.333 0.015 115 287

RWANDA 1962 4.860 0.087 38 1 3.6 0.042 115 39 4.9 0.065 57 6 2.483 0.039 65 129

SAMOA 1976 6.681 0.169 9 -10 5.463 0.11 27 -2 4.317 0.102 7 31

SÃO TOMÉ AND

PRINCIPE 1975 5.203 0.126 24 -2 3.738 0.061 78 25 3.858 0.087 13 42

SAUDI ARABIA 1927 4.319 0.045 85 13 5.263 0.044 72 0 4.12 0.030 150 39 4.033 0.041 24 84

SENEGAL 1960 4.856 0.084 40 1 4.25 0.053 79 19 6.125 0.085 29 -10 3.083 0.049 39 91

SERBIA 2006 4.841 0.631 5 0 5.288 0.056 57 0 6.82 0.076 24 -20 3.850 0.048 24 75

SEYCHELLES 1976 6.449 0.163 11 -9 5.888 0.122 21 -5 4.825 0.115 2 23

SIERRA LEONE 1961 4.745 0.083 41 2 3.613 0.042 116 40 5.445 0.074 43 -2 2.342 0.036 75 145

SINGAPORE 1965 7.223 0.142 7 -16 7.013 0.118 12 -15 6.6 0.104 20 -13 7.133 0.136 -16 3

SLOVAK REPUBLIC 1993 6.833 0.321 4 -6 7 0.29 5 -6 7.94 0.306 2 -9 6.450 0.285 -5 4

SLOVENIA 1992 6.443 0.287 6 -5 7.463 0.299 3 -7 7.705 0.282 3 -9 7.367 0.314 -8 0

SOLOMON ISLANDS 1978 5.621 0.149 17 -5 4.213 0.08 53 13 2.842 0.066 33 70

SOMALIA 1960 0.421 000 ### ### 1.488 9E-18 ##### ##### 1.51 0.000 #DIV/0 #### 0.500 0.001 5786 9000

SOUTH AFRICA 1920 4.904 0.048 68 1 5.288 0.041 77 -1 6.61 0.054 37 -24 4.417 0.042 14 73

SOUTH SUDAN 2011 2.069 0.824 7 3 1.488 4E-16 ##### ##### 3.3 0.597 9 3 0.458 0.000 ### ####

SPAIN 1816 5.024 0.023 135 -4 7.6 0.031 28 -75 6.592 0.031 -51 29

SRI LANKA 1948 3.990 0.055 77 17 5.113 0.057 59 3 4.895 0.051 73 8 2.450 0.030 84 167


35

1 2 3.1 3.2 3.3 3.4 4.1 4.2 4.3 4.4 5.1 5.1 5.3 5.4 6.1 6.2 6.3 6.4

SUDAN 1956 1.332 0.016 429 225 2.488 0.018 335 155 2.35 0.014 434 204 0.767 0.005 795 1265

SURINAME 1975 5.264 0.127 23 -3 5.275 0.102 31 0 4.300 0.099 7 32

SWAZILAND 1968 4.273 0.086 46 8 3.963 0.056 80 23 2.808 0.051 43 92

SWEDEN 1816 6.878 0.033 40 -59 8.3 0.035 5 -87 8.317 0.040 -84 -21

SWITZERLAND 1816 7.288 0.035 26 -68 8.463 0.036 0 -90 8.142 0.039 -81 -17

SYRIAN ARAB REPUBLIC 1961 0.525 0.002 3825 2198 3 0.03 184 76 1.77 0.005 1398 720 1.008 0.010 384 625

TAIWAN, CHINA 1949 6.440 0.094 19 -16 7.7 0.099 8 -25 8.63 0.110 0 -30

TAJIKISTAN 1991 3.105 0.122 42 15 3.9 0.115 40 12 3.585 0.090 56 19 3.050 0.113 17 39

TANZANIA 1961 4.747 0.083 41 2 4.363 0.059 70 15 5.3 0.074 45 0 3.267 0.055 31 77

THAILAND 1887 2.796 0.019 286 113 5.1 0.029 116 6 5.09 0.028 126 7 3.408 0.023 69 176

TIMOR-LESTE 2002 4.354 0.358 11 2 3.85 0.236 20 6 2.450 0.166 15 30

TOGO 1960 4.289 0.073 53 9 3.775 0.044 107 34 4.685 0.059 67 10 2.767 0.043 52 111

TRINIDAD AND TOBAGO 1962 5.169 0.093 32 -3 5.513 0.081 37 -3 5.108 0.089 -1 27

TUNISIA 1956 3.479 0.054 88 27 5.563 0.073 40 -4 5.15 0.063 55 2 3.683 0.056 24 69

TURKEY 1816 3.009 0.013 394 146 5.163 0.019 176 5 7.085 0.028 55 -63 3.792 0.017 72 220

TURKMENISTAN 1991 5.291 0.221 13 -2 4.15 0.127 34 9 2.82 0.057 102 44 3.542 0.134 11 30

UGANDA 1962 3.599 0.062 74 21 3.863 0.048 97 30 6.065 0.088 29 -9 1.917 0.028 110 199

UKRAINE 1991 3.737 0.151 30 8 5 0.167 21 2 5.07 0.155 23 1 3.642 0.138 10 28

UNITED ARAB EMIRATES 1971 6.530 0.145 11 -11 6.238 0.116 19 -8 5.605 0.095 32 -3 6.150 0.132 -9 10

UNITED KINGDOM 1816 5.806 0.027 87 -32 7.563 0.031 29 -74 7.217 0.034 -65 8

UNITED STATES 1816 6.014 0.028 77 -38 6.675 0.026 68 -53 7.058 0.033 -62 13

URUGUAY 1882 6.348 0.045 41 -31 6.725 0.04 43 -36 8.395 0.052 5 -59 6.958 0.049 -40 11

UZBEKISTAN 1991 4.085 0.167 25 5 4.363 0.137 30 7 2.44 0.040 153 71 2.883 0.105 20 44

VENEZUELA, RB 1841 3.205 0.016 308 107 4.925 0.02 176 17 3.56 0.012 428 147 3.450 0.017 90 234

VIETNAM 1954 5.374 0.084 34 -5 5.013 0.061 57 4 4.87 0.056 67 8 3.967 0.058 18 60

YEMEN, REP. 1990 1.085 0.029 246 133 2.713 0.056 103 46 3.8 0.095 51 16 0.992 0.022 180 293

ZAMBIA 1964 5.649 0.107 24 -7 4.55 0.064 61 11 5.725 0.084 34 -5 2.900 0.049 43 94

ZIMBABWE 1965 3.850 0.071 61 15 3.4 0.041 124 46 3.565 0.042 121 41 1.667 0.025 135 236


36

Notes

1. Excludes countries and territories that are not covered in two or more index. (Exception, Greenland as it is the top ranking country in WGI PS&AS).

2. In case of states with multiple dates of ‘entry/exit into the system’ in COW v2011 dataset, the most recent one is taken.

3. WGI Score rescaled to 0-10 (ascending) using the formula: {(New Max - New Min) ÷ (Old Max - Old Min)} x (Current Score – Old Min) + New Min. ‘Old minimum’

and ‘old maximum’ is taken as - 3 and + 3 respectively (inclusive of standard error). New minimum and maximum is 0 and 10 respectively.

4. CIFP fragility score is inverted to ascending order before rescaling. Old minimum and old maximum is 1 and 9 respectively.

5. BTI fragility score is aggregate of Status and Management scores. Thus old minimum and maximum is 0 -20.

6. FSI fragility fragility score is inverted to ascending order before rescaling. Old minimum and old maximum is 0 and 120 respectively.

7. Optimistic pace of progress is obtained by using formula 1 as illustrated in the text.

8. Years to thresholds (i.e. ‘Top’, ‘Global Average’, ‘Stable’ and ‘Sustainable’) is obtained by using formula 2, 3, 4 and 5 as illustrated in the text.

9. The negative values indicate that the particular state has already crossed the specified threshold.

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